{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T13:15:58Z","timestamp":1793884558684,"version":"4.7.0"},"reference-count":38,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2022,11,11]],"date-time":"2022-11-11T00:00:00Z","timestamp":1668124800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2022,11,11]],"date-time":"2022-11-11T00:00:00Z","timestamp":1668124800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,11,11]],"date-time":"2022-11-11T00:00:00Z","timestamp":1668124800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100010109","name":"Medical University of Graz","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100010109","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100010109","name":"Medizinische Universit\u00e4t Graz","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010109","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knee surg. sports traumatol. arthrosc."],"published-print":{"date-parts":[[2023,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>The aims of this study were to (1) analyze the impact of an artificial intelligence (AI)\u2010based computer system on the accuracy and agreement rate of board\u2010certified orthopaedic surgeons (=\u2009senior readers) to detect X\u2010ray features indicative of knee OA in comparison to unaided assessment and (2) compare the results to those of senior residents (=\u2009junior readers).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      One hundred and twenty\u2010four unilateral knee X\u2010rays from the OAI study were analyzed regarding Kellgren\u2013Lawrence grade, joint space narrowing (JSN), sclerosis and osteophyte OARSI grade by computerized methods. Images were rated for these parameters by three senior readers using two modalities: plain X\u2010ray (\n                      <jats:italic>unaided<\/jats:italic>\n                      ) and X\u2010ray presented alongside reports from a computer\u2010assisted detection system (\n                      <jats:italic>aided<\/jats:italic>\n                      ). After exclusion of nine images with incomplete annotation, intraclass correlations between readers were calculated for both modalities among 115 images, and reader performance was compared to ground truth (OAI consensus). Accuracy, sensitivity and specificity were also calculated and the results were compared to those from a previous study on junior readers.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>With the aided modality, senior reader agreement rates for KL grade (2.0\u2010fold), sclerosis (1.42\u2010fold), JSN (1.37\u2010fold) and osteophyte OARSI grades (3.33\u2010fold) improved significantly. Reader specificity and accuracy increased significantly for all features when using the aided modality compared to the gold standard. On the other hand, sensitivity only increased for OA diagnosis, whereas it decreased (without statistical significance) for all other features. With aided analysis, senior readers reached similar agreement and accuracy rates as junior readers, with both surpassing AI performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The introduction of AI\u2010based computer\u2010aided assessment systems can increase the agreement rate and overall accuracy for knee OA diagnosis among board\u2010certified orthopaedic surgeons. Thus, use of this software may improve the standard of care for knee OA detection and diagnosis in the future.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Level of evidence<\/jats:title>\n                    <jats:p>Level II.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00167-022-07220-y","type":"journal-article","created":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T22:02:41Z","timestamp":1668117761000},"page":"1053-1062","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Artificial intelligence\u2010based computer\u2010aided system for knee osteoarthritis assessment increases experienced orthopaedic surgeons\u2019 agreement rate and accuracy"],"prefix":"10.1002","volume":"31","author":[{"given":"Maria Anna","family":"Smolle","sequence":"first","affiliation":[{"name":"<!--<label>1<\/label>--> Department of Orthopaedics and Trauma Medical University of Graz Auenbruggerplatz 5 8036 Graz Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christoph","family":"Goetz","sequence":"additional","affiliation":[{"name":"<!--<label>2<\/label>--> ImageBiopsy Lab Zehetnergasse 6\/2\/2 1140 Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dietmar","family":"Maurer","sequence":"additional","affiliation":[{"name":"<!--<label>3<\/label>--> Department of Orthopaedics Landeskrankenhaus S\u00fcdsteiermark, Standort Radkersburg Dr.\u2010Schwaiger\u2010Stra\u00dfe 1 8490 Bad Radkersburg Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ines","family":"Vielgut","sequence":"additional","affiliation":[{"name":"<!--<label>1<\/label>--> Department of Orthopaedics and Trauma Medical University of Graz Auenbruggerplatz 5 8036 Graz 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Tiago Paixao was employed by ImageBiopsy Lab and declares a conflict of interest. The remaining coauthors have no conflicts of interest to declare.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This study was approved by the local ethics committee and received no specific grant or funding.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}